Cargando…
Implementation of smart social distancing for COVID-19 based on deep learning algorithm
The first step to reducing the effect of viral disease is to prevent the spread which could be achieved by implementing social distancing (reducing the number of close physical interactions between peoples). Almost every viral disease whose means of communication is air, and enters through mouth or...
Autores principales: | Haq, Izaz Ul, Du, Xianjun, Jan, Haseeb |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9019287/ https://www.ncbi.nlm.nih.gov/pubmed/35463218 http://dx.doi.org/10.1007/s11042-022-13154-x |
Ejemplares similares
-
A Review on the Mechanism, Impacts and Control Methods of Membrane Fouling in MBR System
por: Du, Xianjun, et al.
Publicado: (2020) -
Recent Advances in the Prediction of Fouling in Membrane Bioreactors
por: Shi, Yaoke, et al.
Publicado: (2021) -
A deep learning-based social distance monitoring framework for COVID-19
por: Ahmed, Imran, et al.
Publicado: (2021) -
Smart Distance Lab’s art fair, experimental data on social distancing during the COVID-19 pandemic
por: Tanis, Charlotte C., et al.
Publicado: (2021) -
Deep Learning Assisted Buildings Energy Consumption Profiling Using Smart Meter Data
por: Ullah, Amin, et al.
Publicado: (2020)